ResearchPad - coronavirus https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[New Zealand's success]]> https://www.researchpad.co/article/elastic_article_13520 The country is tantalisingly close to wiping out covid-19. Does that mean life there can go back to normal? Alice Klein reports

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<![CDATA[Rethinking testing]]> https://www.researchpad.co/article/elastic_article_12955 Instead of just testing people with symptoms, many countries could benefit from weekly testing of all key workers, reports Michael Le Page

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<![CDATA[New biometric products flood out to tackle Covid-19]]> https://www.researchpad.co/article/elastic_article_10628 Contactless biometric systems aimed at combatting the Covid-19 virus are being launched at a significant rate – and adopted by high-profile users ranging from the United Nations to the Chinese police.

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<![CDATA[Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29<sup>th</sup>–March 30<sup>th</sup>, 2020]]> https://www.researchpad.co/article/elastic_article_8469 The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru.

We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place.

Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.96 (95% CI: 0.87, 1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government.

While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

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<![CDATA[The Consequences of Neoliberalism in the Current Pandemic]]> https://www.researchpad.co/article/elastic_article_8014 This article analyzes how the neoliberal policies, such as the politics of austerity (with considerable cuts to social policy expenditures including medical care and public health services) and the privatization of health services, imposed by many governments on both sides of the North Atlantic, considerably weakened the capacity of the response to the coronavirus pandemic in Italy, Spain, and the United States.

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<![CDATA[Digesting the crisis: autophagy and coronaviruses]]> https://www.researchpad.co/article/N14e3723f-733f-4d90-9494-31489cab3f33 Autophagy is a catabolic pathway with multifaceted roles in cellular homeostasis. This process is also involved in the antiviral response at multiple levels, including the direct elimination of intruding viruses (virophagy), the presentation of viral antigens, the fitness of immune cells, and the inhibition of excessive inflammatory reactions. In line with its central role in immunity, viruses have evolved mechanisms to interfere with or to evade the autophagic process, and in some cases, even to harness autophagy or constituents of the autophagic machinery for their replication. Given the devastating consequences of the current COVID-19 pandemic, the question arises whether manipulating autophagy might be an expedient approach to fight the novel coronavirus SARS-CoV-2. In this piece, we provide a short overview of the evidence linking autophagy to coronaviruses and discuss whether such links may provide actionable targets for therapeutic interventions.

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<![CDATA[Etymologia: Coronavirus]]> https://www.researchpad.co/article/N5d3f23c8-e3c5-4daf-82fc-7d119de62410 ]]> <![CDATA[Serologic Detection of Middle East Respiratory Syndrome Coronavirus Functional Antibodies]]> https://www.researchpad.co/article/N158cbcf2-1e1c-4f67-aeb3-be6726051b89

We developed and validated 2 species-independent protein-based assays to detect Middle East respiratory syndrome coronavirus functional antibodies that can block virus receptor-binding or sialic acid-attachment. Antibody levels measured in both assays correlated strongly with virus-neutralizing antibody titers, proving their use for serologic confirmatory diagnosis of Middle East respiratory syndrome.

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<![CDATA[Risk for Transportation of Coronavirus Disease from Wuhan to Other Cities in China]]> https://www.researchpad.co/article/N00c6f358-68ee-40be-ba1e-812b37277a1d

On January 23, 2020, China quarantined Wuhan to contain coronavirus disease (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 other cities in China before the quarantine. Expected COVID-19 risk is >50% in 130 (95% CI 89–190) cities and >99% in the 4 largest metropolitan areas.

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<![CDATA[The SARS-CoV-2 receptor ACE2 expression of maternal-fetal interface and fetal organs by single-cell transcriptome study]]> https://www.researchpad.co/article/N6fc22072-15f3-4c64-b34f-34474f5cf931

The new type of pneumonia caused by the SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) has been declared as a global public health concern by WHO. As of April 3, 2020, more than 1,000,000 human infections have been diagnosed around the world, which exhibited apparent person-to-person transmission characteristics of this virus. The capacity of vertical transmission in SARS-CoV-2 remains controversial recently. Angiotensin-converting enzyme 2 (ACE2) is now confirmed as the receptor of SARS-CoV-2 and plays essential roles in human infection and transmission. In present study, we collected the online available single-cell RNA sequencing (scRNA-seq) data to evaluate the cell specific expression of ACE2 in maternal-fetal interface as well as in multiple fetal organs. Our results revealed that ACE2 was highly expressed in maternal-fetal interface cells including stromal cells and perivascular cells of decidua, and cytotrophoblast and syncytiotrophoblast in placenta. Meanwhile, ACE2 was also expressed in specific cell types of human fetal heart, liver and lung, but not in kidney. And in a study containing series fetal and post-natal mouse lung, we observed ACE2 was dynamically changed over the time, and ACE2 was extremely high in neonatal mice at post-natal day 1~3. In summary, this study revealed that the SARS-CoV-2 receptor was widely spread in specific cell types of maternal-fetal interface and fetal organs. And thus, both the vertical transmission and the placenta dysfunction/abortion caused by SARS-CoV-2 need to be further carefully investigated in clinical practice.

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<![CDATA[The effect of human mobility and control measures on the COVID-19 epidemic in China]]> https://www.researchpad.co/article/Neabfc182-1d9f-47b2-b5e8-bfec14d78739

The ongoing COVID-19 outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions have been undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.

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<![CDATA[An orally bioavailable broad-spectrum antiviral inhibits SARS-CoV-2 in human airway epithelial cell cultures and multiple coronaviruses in mice]]> https://www.researchpad.co/article/Nc775bb5e-e6b3-4fd5-a2ba-092b072f375a

Coronaviruses (CoVs) traffic frequently between species resulting in novel disease outbreaks, most recently exemplified by the newly emerged SARS-CoV-2, the causative agent of COVID-19. Herein, we show that the ribonucleoside analog β-D-N4-hydroxycytidine (NHC, EIDD-1931) has broad spectrum antiviral activity against SARS-CoV-2, MERS-CoV, SARS-CoV, and related zoonotic group 2b or 2c Bat-CoVs, as well as increased potency against a coronavirus bearing resistance mutations to the nucleoside analog inhibitor remdesivir. In mice infected with SARS-CoV or MERS-CoV, both prophylactic and therapeutic administration of EIDD-2801, an orally bioavailable NHC-prodrug (β-D-N4-hydroxycytidine-5′-isopropyl ester), improved pulmonary function, and reduced virus titer and body weight loss. Decreased MERS-CoV yields in vitro and in vivo were associated with increased transition mutation frequency in viral but not host cell RNA, supporting a mechanism of lethal mutagenesis in CoV. The potency of NHC/EIDD-2801 against multiple coronaviruses and oral bioavailability highlight its potential utility as an effective antiviral against SARS-CoV-2 and other future zoonotic coronaviruses.

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<![CDATA[Coronavirus infections: Epidemiological, clinical and immunological features and hypotheses]]> https://www.researchpad.co/article/N8b1030d3-df39-42d9-a725-e3c11c00213e

Coronaviruses (CoVs) are a large family of enveloped, positive-strand RNA viruses. Four human CoVs (HCoVs), the non-severe acute respiratory syndrome (SARS)-like HCoVs (namely HCoV 229E, NL63, OC43, and HKU1), are globally endemic and account for a substantial fraction of upper respiratory tract infections. Non-SARS-like CoV can occasionally produce severe diseases in frail subjects but do not cause any major (fatal) epidemics. In contrast, SARS like CoVs (namely SARS-CoV and Middle-East respiratory syndrome coronavirus, MERS-CoV) can cause intense short-lived fatal outbreaks. The current epidemic caused by the highly contagious SARS-CoV-2 and its rapid spread globally is of major concern. There is scanty knowledge on the actual pandemic potential of this new SARS-like virus. It might be speculated that SARS-CoV-2 epidemic is grossly underdiagnosed and that the infection is silently spreading across the globe with two consequences: (i) clusters of severe infections among frail subjects could haphazardly occur linked to unrecognized index cases; (ii) the current epidemic could naturally fall into a low-level endemic phase when a significant number of subjects will have developed immunity. Understanding the role of paucisymptomatic subjects and stratifying patients according to the risk of developing severe clinical presentations is pivotal for implementing reasonable measures to contain the infection and to reduce its mortality. Whilst the future evolution of this epidemic remains unpredictable, classic public health strategies must follow rational patterns. The emergence of yet another global epidemic underscores the permanent challenges that infectious diseases pose and underscores the need for global cooperation and preparedness, even during inter-epidemic periods.

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<![CDATA[Propagation analysis and prediction of the COVID-19]]> https://www.researchpad.co/article/N8eed231d-a3c4-460f-9998-75e54b9c5a58

Based on the official data modeling, this paper studies the transmission process of the Corona Virus Disease 2019 (COVID-19). The error between the model and the official data curve is quite small. At the same time, it realized forward prediction and backward inference of the epidemic situation, and the relevant analysis help relevant countries to make decisions.

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<![CDATA[The Coming Coronavirus Crisis: What Can We Learn?]]> https://www.researchpad.co/article/Nb5a9a092-ee0d-47aa-a4ea-ac963f7bddbc

The coronavirus pandemic is bringing with it the prospect of severe financial and economic crises. The article investigates its economic consequences in terms of financial instability, economic recession, lower incomes and policy challenges at the national and European levels. What are some of the lessons that can be learned? This article argues that health is a global public good. Public health and welfare systems are crucial alternatives to the market and universal public health is a key element of an egalitarian policy.

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<![CDATA[New coronavirus outbreak. Lessons learned from the severe acute respiratory syndrome epidemic]]> https://www.researchpad.co/article/N09c9b2c8-e2b6-47f4-b1cb-8fa55f00f9ef

SUMMARY

System dynamics approach offers great potential for addressing how intervention policies can affect the spread of emerging infectious diseases in complex and highly networked systems. Here, we develop a model that explains the severe acute respiratory syndrome coronavirus (SARS-CoV) epidemic that occurred in Hong Kong in 2003. The dynamic model developed with system dynamics methodology included 23 variables (five states, four flows, eight auxiliary variables, six parameters), five differential equations and 12 algebraic equations. The parameters were optimized following an iterative process of simulation to fit the real data from the epidemics. Univariate and multivariate sensitivity analyses were performed to determine the reliability of the model. In addition, we discuss how further testing using this model can inform community interventions to reduce the risk in current and future outbreaks, such as the recently Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic.

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<![CDATA[Why is it difficult to accurately predict the COVID-19 epidemic?]]> https://www.researchpad.co/article/Nfef213eb-1508-48fb-b79f-0644c88064d2

Since the COVID-19 outbreak in Wuhan City in December of 2019, numerous model predictions on the COVID-19 epidemics in Wuhan and other parts of China have been reported. These model predictions have shown a wide range of variations. In our study, we demonstrate that nonidentifiability in model calibrations using the confirmed-case data is the main reason for such wide variations. Using the Akaike Information Criterion (AIC) for model selection, we show that an SIR model performs much better than an SEIR model in representing the information contained in the confirmed-case data. This indicates that predictions using more complex models may not be more reliable compared to using a simpler model. We present our model predictions for the COVID-19 epidemic in Wuhan after the lockdown and quarantine of the city on January 23, 2020. We also report our results of modeling the impacts of the strict quarantine measures undertaken in the city after February 7 on the time course of the epidemic, and modeling the potential of a second outbreak after the return-to-work in the city.

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<![CDATA[Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020]]> https://www.researchpad.co/article/Ne00ead13-ea6f-4654-adc5-7cb9ff13ce2c

The initial cluster of severe pneumonia cases that triggered the COVID-19 epidemic was identified in Wuhan, China in December 2019. While early cases of the disease were linked to a wet market, human-to-human transmission has driven the rapid spread of the virus throughout China. The Chinese government has implemented containment strategies of city-wide lockdowns, screening at airports and train stations, and isolation of suspected patients; however, the cumulative case count keeps growing every day. The ongoing outbreak presents a challenge for modelers, as limited data are available on the early growth trajectory, and the epidemiological characteristics of the novel coronavirus are yet to be fully elucidated.

We use phenomenological models that have been validated during previous outbreaks to generate and assess short-term forecasts of the cumulative number of confirmed reported cases in Hubei province, the epicenter of the epidemic, and for the overall trajectory in China, excluding the province of Hubei. We collect daily reported cumulative confirmed cases for the 2019-nCoV outbreak for each Chinese province from the National Health Commission of China. Here, we provide 5, 10, and 15 day forecasts for five consecutive days, February 5th through February 9th, with quantified uncertainty based on a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model.

Our most recent forecasts reported here, based on data up until February 9, 2020, largely agree across the three models presented and suggest an average range of 7409–7496 additional confirmed cases in Hubei and 1128–1929 additional cases in other provinces within the next five days. Models also predict an average total cumulative case count between 37,415 and 38,028 in Hubei and 11,588–13,499 in other provinces by February 24, 2020.

Mean estimates and uncertainty bounds for both Hubei and other provinces have remained relatively stable in the last three reporting dates (February 7th – 9th). We also observe that each of the models predicts that the epidemic has reached saturation in both Hubei and other provinces. Our findings suggest that the containment strategies implemented in China are successfully reducing transmission and that the epidemic growth has slowed in recent days.

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<![CDATA[An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)]]> https://www.researchpad.co/article/N6a6056b1-3479-4fb6-9569-57adefa5c776

The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known that the estimation of this number may vary due to several methodological issues, including different assumptions and choice of parameters, utilized models, used datasets and estimation period. With the spreading of the novel coronavirus (2019-nCoV) infection, the reproduction number has been found to vary, reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies that have been rapidly improved, enabling to shorten the time from infection/symptoms onset to diagnosis, leading to faster confirmation of the new coronavirus cases, our previous estimations on the transmission risk of the 2019-nCoV need to be revised. By using time-dependent contact and diagnose rates, we refit our previously proposed dynamics transmission model to the data available until January 29th, 2020 and re-estimated the effective daily reproduction ratio that better quantifies the evolution of the interventions. We estimated when the effective daily reproduction ratio has fallen below 1 and when the epidemics will peak. Our updated findings suggest that the best measure is persistent and strict self-isolation. The epidemics will continue to grow, and can peak soon with the peak time depending highly on the public health interventions practically implemented.

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<![CDATA[Middle East Respiratory Syndrome Coronavirus Transmission ]]> https://www.researchpad.co/article/Nae752aa4-97a9-4010-84c2-ed1cdca5a47a

Middle East respiratory syndrome coronavirus (MERS-CoV) infection causes a spectrum of respiratory illness, from asymptomatic to mild to fatal. MERS-CoV is transmitted sporadically from dromedary camels to humans and occasionally through human-to-human contact. Current epidemiologic evidence supports a major role in transmission for direct contact with live camels or humans with symptomatic MERS, but little evidence suggests the possibility of transmission from camel products or asymptomatic MERS cases. Because a proportion of case-patients do not report direct contact with camels or with persons who have symptomatic MERS, further research is needed to conclusively determine additional mechanisms of transmission, to inform public health practice, and to refine current precautionary recommendations.

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